Adherence to Practice Guidelines for Transient Ischemic Attacks in an Emergency Department
Bibliographic record
Abstract
OBJECTIVE: To evaluate the investigation and treatment of patients with a diagnosis of transient ischemic attacks (TIA) in the emergency department (ED) a tertiary care teaching hospital with a neuroscience referral program. METHODS: A chart review was conducted in the hospital. Consecutive ED charts with a diagnosis of TIA were included; each was reviewed by independent coders using a standardized data form. RESULTS: Two hundred and ninety-three TIA charts were reviewed; the gender ratio was 1:1 with a mean age of 66 years. Most patients (75%; 95% CI: 70, 80) were evaluated by ED physicians; the remaining patients were seen directly by referral services. The median time from symptom onset to ED arrival was 29 hours and the duration of symptoms was 4.6 hours. Most patients received CT scans (81%; 95% CI: 73, 85), complete blood counts (74%; 95% CI: 68, 79), and electrocardiograms (75%; 95% CI: 70, 80) in the ED. In 16% (95% CI: 13, 22) a carotid doppler was performed and in 26% (95% CI: 21, 31) an outpatient doppler was booked. Among those who were discharged (75%; 95% CI: 70, 80), antithrombotic medications were not prescribed to 28% (95% CI: 22, 34). CONCLUSION: Practice variation exists with respect to the investigation and treatment of TIAs in this tertiary-care teaching hospital. Carotid doppler investigation and use of anti-platelet therapy for patients with TIA are suboptimal. Clinical practice guidelines and rapid assessment TIA clinics may change these results.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.066 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".